请写一段代码，利用libjpeg库实现对图像的双边滤波处理。

这里给出一个简单的利用libjpeg库实现对图像的双边滤波处理的C语言代码示例：

#include <stdio.h>
#include <stdlib.h>
#include <jpeglib.h>
#include <jerror.h>
#include <math.h>

// 定义双边滤波函数
void bilateral_filter(unsigned char *src_data, unsigned char *dst_data, int width, int height, int channels, int radius, double sigma_d, double sigma_r)
{
    int window_size = 2 * radius + 1;
    double *w_d = (double *)malloc(sizeof(double) * window_size * window_size);
    double *w_r = (double *)malloc(sizeof(double) * window_size * window_size);
    double weight_d, weight_r, weight_sum;
    double pixel_value;
    int offset, i, j, k, l, m, n;
    int x, y, x1, y1, x2, y2;
    int neighbor_x, neighbor_y;
    int src_index, dst_index;

    for (y = 0; y < height; y++) {
        for (x = 0; x < width; x++) {
            offset = (y * width + x) * channels;
            weight_sum = 0.0;
            pixel_value = 0.0;

            for (i = -radius; i <= radius; i++) {
                for (j = -radius; j <= radius; j++) {
                    x1 = x + i;
                    y1 = y + j;

                    if (x1 < 0 || x1 >= width || y1 < 0 || y1 >= height) {
                        continue;
                    }

                    x2 = x1 - x;
                    y2 = y1 - y;
                    weight_d = exp(-(x2 * x2 + y2 * y2) / (2.0 * sigma_d * sigma_d));
                    neighbor_x = src_data[(y1 * width + x1) * channels];
                    neighbor_y = src_data[(y1 * width + x1) * channels + 1];
                    neighbor_z = src_data[(y1 * width + x1) * channels + 2];
                    weight_r = exp(-(neighbor_x - src_data[offset]) * (neighbor_x - src_data[offset]) / (2.0 * sigma_r * sigma_r));
                    weight_r *= exp(-(neighbor_y - src_data[offset + 1]) * (neighbor_y - src_data[offset + 1]) / (2.0 * sigma_r * sigma_r));
                    weight_r *= exp(-(neighbor_z - src_data[offset + 2]) * (neighbor_z - src_data[offset + 2]) / (2.0 * sigma_r * sigma_r));
                    w_d[(j + radius) * window_size + (i + radius)] = weight_d;
                    w_r[(j + radius) * window_size + (i + radius)] = weight_r;
                    weight_sum += weight_d * weight_r;
                    pixel_value += weight_d * weight_r * src_data[offset + j * width * channels + i * channels];
                }
            }

            dst_data[offset] = pixel_value / weight_sum;
            dst_data[offset + 1] = pixel_value / weight_sum;
            dst_data[offset + 2] = pixel_value / weight_sum;
        }
    }

    free(w_d);
    free(w_r);
}

// 主函数
int main()
{
    struct jpeg_decompress_struct cinfo;
    struct jpeg_error_mgr jerr;
    FILE *infile;
    JSAMPARRAY buffer;
    int row_stride;

    // 打开JPEG文件
    if ((infile = fopen("input.jpg", "rb")) == NULL) {
        fprintf(stderr, "can't open input file\n");
        return 0;
    }

    // 初始化JPEG解压对象
    cinfo.err = jpeg_std_error(&jerr);
    jpeg_create_decompress(&cinfo);
    jpeg_stdio_src(&cinfo, infile);
    jpeg_read_header(&cinfo, TRUE);
    jpeg_start_decompress(&cinfo);

    // 读取JPEG图像数据
    row_stride = cinfo.output_width * cinfo.output_components;
    buffer = (*cinfo.mem->alloc_sarray)((j_common_ptr)&cinfo, JPOOL_IMAGE, row_stride, 1);
    unsigned char *data = (unsigned char *)malloc(cinfo.output_width * cinfo.output_height * cinfo.output_components);
    unsigned char *output_data = (unsigned char *)malloc(cinfo.output_width * cinfo.output_height * cinfo.output_components);

    while (cinfo.output_scanline < cinfo.output_height) {
        jpeg_read_scanlines(&cinfo, buffer, 1);
        memcpy(data + row_stride * (cinfo.output_scanline - 1), buffer[0], row_stride);
    }

    // 关闭JPEG解压对象
    jpeg_finish_decompress(&cinfo);
    jpeg_destroy_decompress(&cinfo);
    fclose(infile);

    // 对图像进行双边滤波
    bilateral_filter(data, output_data, cinfo.output_width, cinfo.output_height, cinfo.output_components, 5, 10.0, 100.0);

    // 将结果保存为JPEG文件
    struct jpeg_compress_struct dstinfo;
    struct jpeg_error_mgr dsterr;
    FILE *outfile;
    JSAMPROW row_pointer[1];
    int dst_row_stride;

    if ((outfile = fopen("output.jpg", "wb")) == NULL) {
        fprintf(stderr, "can't open output file\n");
        return 0;
    }

    dstinfo.err = jpeg_std_error(&dsterr);
    jpeg_create_compress(&dstinfo);
    jpeg_stdio_dest(&dstinfo, outfile);
    dstinfo.image_width = cinfo.output_width;
    dstinfo.image_height = cinfo.output_height;
    dstinfo.input_components = cinfo.output_components;
    dstinfo.in_color_space = cinfo.out_color_space;
    jpeg_set_defaults(&dstinfo);
    jpeg_start_compress(&dstinfo, TRUE);
    dst_row_stride = dstinfo.image_width * dstinfo.input_components;
    row_pointer[0] = (JSAMPROW)malloc(dst_row_stride);

    while (dstinfo.next_scanline < dstinfo.image_height) {
        for (int i = 0; i < dst_row_stride; i++) {
            row_pointer[0][i] = output_data[dstinfo.next_scanline * dst_row_stride + i];
        }

        jpeg_write_scanlines(&dstinfo, row_pointer, 1);
    }

    jpeg_finish_compress(&dstinfo);
    jpeg_destroy_compress(&dstinfo);
    fclose(outfile);

    // 释放内存
    free(data);
    free(output_data);
    free(row_pointer[0]);

    return 0;
}

需要注意的是，这里的双边滤波函数只支持处理RGB三通道图像，如果需要处理其他类型的图像，需要进行相应的修改。在使用时，需要将`input.jpg`和`output.jpg`替换为实际的JPEG图像文件名。